Autonomous collision avoidance system for unmanned aerial vehicles

ABSTRACT

Autonomous collision avoidance systems for unmanned aerial vehicles are disclosed. Systems illustratively include a detect and track module, an inertial navigation system, and an auto avoidance module. The detect and track module senses a potential object of collision and generates a moving object track for the potential object of collision. The inertial navigation system provides information indicative of a position and a velocity of the unmanned aerial vehicle. The auto avoidance module receives the moving object track for the potential object of collision and the information indicative of the position and the velocity of the unmanned aerial vehicle. The auto avoidance module utilizes the information to generate a guidance maneuver that facilitates the unmanned aerial vehicle avoiding the potential object of collision.

REFERENCE TO RELATED CASE

The present application is a continuation of and claims the priority ofapplication Ser. No. 10/872,144 filed on Jun. 18, 2004, the content ofwhich is hereby incorporated by reference in its entirety.

BACKGROUND

Many vehicles, such as aircraft vehicles, have systems which use radarfor detecting potential objects of collision, such as terrain and othervehicles. Radar can detect potential objects of collision located withina certain proximity to the aircraft vehicle. Upon radar detecting thepresence of a potential object of collision, a warning signal isprovided to a pilot of the aircraft. The pilot must then analyze theobject and determine if action needs to be taken in order to avoid theobject. If action needs to be taken, the pilot obeys general aviationand etiquette rules promulgated by the FAA (Federal AviationAdministration) to regulate aircraft vehicle traffic in national airspace (NAS).

These types of conventional avoidance systems are very expensive.Therefore, integrating such a system on smaller vehicles is not entirelyfeasible. In addition, these conventional avoidance systems detectpotential objects of collision and provide warning signals only. Thus,conventional avoidance systems rely on the presence of a pilot torecognize the signal and take appropriate action by altering the courseof the vehicle.

The potential for collisions is even greater in the context of unmannedvehicle systems. In one application of such a technology, a remotelylocated operator manages and controls an unmanned aerial vehicle (UAV),typically from a ground control station. Although the ground controlstation enables some degree of controlled flight, generally, UAVs lackthe ability to scout out their surrounding airspace and watch forincoming obstacles. Even if a UAV is equipped with some sort offorward-looking camera or video capability, the remotely locatedoperator is primarily focused on payload and mission operations and hasa limited ability to accurately interpret and analyze video information.In addition, under the circumstances, a remotely located operator mayhave a difficult time complying with the FAA rules for flying incivilian airspace.

Currently, UAVs are not allowed to fly in NAS. In particular, UAVs arenot allowed to fly in any air space unless the UAV has received FAAapproval. One of the most significant technology barriers forintegrating UAVs into NAS is an effective and reliable collisionavoidance system. Overcoming this technology barrier will openbeneficial services to the national civilian marketplace such as forestmanagement, mineral surveys, border patrol, agriculture and pipeline andpower line inspections. Beyond these and other specific potential UAVmarkets, an effective and reliable collision avoidance system canprovide pilots an additional mechanism to safely fly manned aircraft.

SUMMARY

Embodiments of the present disclosure include autonomous collisionavoidance systems for unmanned aerial vehicles. Systems illustrativelyinclude a detect and track module, an inertial navigation system, and anauto avoidance module. The detect and track module senses a potentialobject of collision and generates a moving object track for thepotential object of collision. The inertial navigation system providesinformation indicative of a position and a velocity of the unmannedaerial vehicle. The auto avoidance module receives the moving objecttrack for the potential object of collision and the informationindicative of the position and the velocity of the unmanned aerialvehicle. The auto avoidance module utilizes the information to generatea guidance maneuver that facilitates the unmanned aerial vehicleavoiding the potential object of collision.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a simplified block diagram of a collision avoidancesystem in accordance with an embodiment of the present invention.

FIG. 2 illustrates a simplified block diagram of an auto avoidancemodule in accordance with an embodiment of the present invention.

FIG. 3 illustrates an earth centered, earth fixed (ECEF) referenceframe.

FIG. 4-1 illustrates a geodetic reference frame and local verticalcoordinate frame.

FIG. 4-2 illustrates a local vertical reference frame with respect to ageodetic reference frame.

FIG. 5 illustrates a local vertical reference frame and line of sightreference frame.

FIG. 6 illustrates a guidance logic routine in accordance with anembodiment of the present invention.

DETAILED DESCRIPTION

Much of the description of the present invention will be devoted todescribing embodiments in the context of unmanned aerial vehicles (UAV).However, it is to be understood that the embodiments of the presentinvention pertain to a collision avoidance system and are designed forbroad application. The embodiments can be adapted by one skilled in theart to be applied in the context of any of a variety of unmanned andmanned vehicles including, but not limited to, airplanes, helicopters,missiles, submarines, balloons or dirigibles, wheeled road vehicles,tracked ground vehicles (i.e., tanks), and the like.

FIG. 1 illustrates a simplified block diagram of autonomously controlledcollision avoidance system 100 as implemented in a UAV 102 in accordancewith an embodiment of the present invention. Collision avoidance system100 includes a detect and track module 104 coupled to an auto avoidancemodule 106 which is in communication with a ground control station 108,an inertial navigation system 105 and flight controls 114.

Detect and track module 104 includes sensors 110 and moving targetdetection and tracking module 112. In one embodiment, sensors 110include video or optical cameras that use visible-light wavelengthdetector arrays and can optically sense various objects within aparticular range depending at least on camera quality and resolutioncapability. Sensors 110 are configured to take real-time video,typically digital video, of the environment in which UAV 102 is flying.For example, the video is provided to moving target detection andtracking module 112. In another embodiment, sensors 110 could benon-visual sensors, such as radio frequency (RF), laser, infrared (IR)or sonar. Module 112, using sensed information, is configured to providemoving object tracks to auto avoidance module 106. Inertial navigationsystem 105 provides auto avoidance 106 with information related tovelocity, position and angular position of UAV 102.

Based on the moving object tracks provided by detect and track 104 andinformation provided by inertial navigation system 105, auto avoidancemodule 106 is able to generate the best estimate of position andvelocity for the object of collision. Auto avoidance module 106 alsocalculates various relative or navigational states of the object ofcollision with respect to UAV 102 and generates guidance maneuvercommands for flight controls 114 to avoid the potential object ofcollision. In addition, module 106 communicates with ground controlstation 108. Module 106 can relay status information, such asinformation related to position and velocity of UAV 102 and informationrelated to the potential object of collision, to ground control station108 through an operator interface 116. In accordance with oneembodiment, the navigational status information alerts an operator thatUAV 102 is on a course to collide with an object. Relaying statusinformation gives the operator a chance to take over flight controls 114to manually avoid the object and/or notify the operator that UAV 102will enter an auto avoidance guidance mode. The status information alsorelays information related to potential objects of collision to asituation awareness display 118 via operator interface 116.

Situational awareness display 118 illustratively displays syntheticimagery of operator situational awareness. For example, situationalawareness display 118 incorporates commercial off-the-shelf technologydeveloped by SDS International of Arlington, Va. The synthetic imageryillustratively provides synthetic real-time displays of two-dimensionaland/or three-dimensional views of UAV 102 and its surroundings as itflies within a particular airspace. For example, if current weatherconditions are hazy or cloudy, the synthetic imagery displays UAV 102 ina clear synthetic corresponding environment. Auto avoidance module 106provides information about a potential object of collision to situationawareness display 118 such that ground control station 108 can instructsituation awareness display 118 to generate visuals of objects based onthe real-time position of the objects.

FIG. 2 illustrates a simplified block diagram of auto avoidance module106 and inertial navigation system 105 in accordance with an embodimentof the present invention. Auto avoidance module 106 includes a trackstate estimator 120. Track state estimator 120, in the currentembodiment, is configured to receive moving object tracks in the form ofelevation ε_(el) and azimuth ε_(az) direction finding (DF) angleinformation relative to the visual sensor bore sight. It should be notedthat those skilled in the art could incorporate other track stateinformation from detect and track module 112 in track state estimator120. For example, range, closing velocity (V_(C)) and DF rates can beincorporated from detect and track module 112. Track state estimator 120is also configured to receive estimations of position and velocity forUAV 102 provided by inertial navigation system 105. Inertial navigationsystem 105 includes a global positioning system (GPS) 132 and aninertial measurement unit 134. These sensors are coupled with strapdownequations and a sensor error estimator such that the best estimate ofposition, velocity and angular position are determined for UAV 102. Inaddition, information determined by inertial navigation system 105 isalso configured to be received by auto avoid guidance 128 to aid inguiding UAV 102 away from an object of collision. Track state estimator120 uses the DF angle information and the best estimate of position andvelocity of UAV 102 to estimate the relative range vector R, therelative range rate vector {dot over ( R, a line-of-sight angle vector λ_(LOS) and a line-of-sight rate vector {dot over ( λ _(LOS) between UAV102 and the potential object of collision.

In accordance with one embodiment of the present invention, track stateestimator 120 is an Extended Kalman Filter. Extended Kalman Filters arewell known in the art. A detailed discussion of Extended Kalman Filtersis described in the article by Taek L. Song et al. titled “SuboptimalFilter Design with Pseudomeasurements for Target Tracking”. 1988. IEEETransactions on Aerospace and Electronic Systems. Vol. 24. However,those skilled in the art should recognize that track state estimator 120can utilize other types of mathematical systems that provide estimationsof past, present and future states of an object based on DF anglesobtained by various types of sensors.

The information determined and provided by track state estimator 120 isreceived by auto avoid monitor 122 to determine various parameters thatforecast future collisions and received by auto avoid guidance 128 todevelop guidance commands that divert the path of UAV 102 to avoid sucha collision. Auto avoid monitor 122 includes an avoid state calculator124 and an avoid alert calculator 126. Avoid state calculator 124 takesthe information estimated by track state estimator 120 and calculatesvarious navigational states. For example, avoid state calculator 124determines a time-to-go) (t_(go)) to the closest point of approach basedon current velocity and range profiles, the relative closing velocity(V_(C)) along the line of sight between the object and UAV 102 and thezero effort miss distance (ZEM) or closest point of approach based onnon-accelerated current velocity and range profiles. Currently, FAAguidelines require that a vehicle must miss another vehicle by 500 feet.Thus, the avoidance maneuver of the present invention illustrativelyguarantees at least a 500-foot miss (of course, any other range iswithin the scope of the present invention). In addition, the minimummiss distance or ZEM is used as an indicator to terminate the avoidancemaneuver and return UAV 102 to its prior path.

Avoid alert calculator 126 calculates an alert avoid flag and a head-onflag based on ZEM. The head-on flag indicates that UAV 102 is on courseto collide with the potential object of collision head-on. The alertavoid flag indicates that UAV 102 is on course to enter in to some othertype of collision. Both head-on flag and alert avoid flag shouldactivate auto avoid guidance 128 to avoid an object. Auto avoid guidance128 receives the calculated parameters from avoid state calculator 124,the alert avoid flag as well as the head-on indicator to override theexisting guidance mode of UAV 102. Auto avoid guidance 128 maneuvers UAV102 by generating avoidance maneuver commands for flight controls 114 toavoid a collision and miss an approaching object by at least thepredetermined miss distance. Auto avoid guidance 128 can also use anactive transponder system, used in commercial aviation, to injectcommands into auto avoid guidance module 128.

In accordance with one embodiment, auto avoid guidance 128 is programmedto make an avoidance maneuver according to the FAA's “rules of the road”for civilian aircraft operating in National Air Space (NAS). Inparticular, the avoidance maneuver complies with Part 91 of the FAAregulations and meets the FAA's Collision Avoidance Systems Final RuleFAA-2001-10910-487 and FAA 2001-10910-489. After auto avoid guidance 128completes a maneuver, auto avoid recovery 130 generates recoverycommands for flight controls 114 such that UAV 102 gracefully resumesthe previous guidance mode.

FIG. 3 illustrates an earth centered, earth fixed (ECEF) reference frame300. ECEF reference frame 300 is oriented with its origin at the earthcenter, wherein the x-axis and the y-axis lie in the equatorial plane302 with the x-axis passing through the Greenwich Meridian 304. Thez-axis is normal to the x-y plane and passes through the North Pole 306.

FIG. 4-1 illustrates a geodetic reference frame 400 that defines thelines of latitude λ and longitude l along the earth's surface. Geodeticlatitude λ is the angle between the equatorial plane 402 and the normalto the surface of an ellipsoid. Geodetic longitude l is the angularrotation relative to the ECEF x-axis in the equatorial plane 402.Geodetic altitude h (not shown) is the elevation above the ellipsoidsurface.

FIG. 4-2 illustrates a local vertical coordinate frame 404 with respectto the geodetic reference frame 400. The local vertical reference frame404 is illustrated as a north, east, down (NED) reference frame. The NEDreference frame is a right handed, orthogonal coordinate system orientedat the surface of the Earth's ellipsoid. The z-axis is tangent to thenormal of the Earth surface ellipsoid and has its positive directionpointing into earth. The positive x-axis points towards true north andthe positive y-axis points towards the East.

Certain embodiments of the present invention involve coordinate frametransformations. For example, a function can be applied to transformlocal vertical (NED) coordinates to body frame coordinates. In thisexample transformation, the following 3×3 transformation matrix (TBLMatrix):

$\begin{matrix}{{TBL} = \begin{bmatrix}{\cos \; \psi \; \cos \; \theta} & {\sin \; {\psi cos}\; \theta} & {{- \sin}\; \theta} \\\begin{matrix}{\left( {\cos \; {\psi sin\theta sin}\; \varphi} \right) +} \\\left( {\sin \; {\psi cos\varphi}} \right)\end{matrix} & \begin{matrix}{\left( {\sin \; {\psi sin}\; {\theta sin\varphi}} \right) +} \\\left( {\cos \; \psi \; \cos \; \theta} \right)\end{matrix} & {\cos \; {\theta sin}\; \varphi} \\\begin{matrix}{\left( {\cos \; {\psi sin\theta cos}\; \varphi} \right) +} \\\left( {\sin \; {\psi sin}\; \varphi} \right)\end{matrix} & \begin{matrix}{\left( {\sin \; {\psi sin}\; {\theta cos\varphi}} \right) -} \\\left( {\cos \; \psi \; \sin \; \varphi} \right)\end{matrix} & {\cos \; \theta \; \cos \; \varphi}\end{bmatrix}} & {{Equation}\mspace{14mu} 1}\end{matrix}$

where θ is the pitch angle, Ψ is the yaw angle and φ is the roll angleof UAV 102.

FIG. 5 illustrates a local vertical coordinate frame showing the north,east and down (NED) components relative to UAV 102 and an object ofcollision 103. In addition, FIG. 5 illustrates a line of sight (LOS)coordinate frame, wherein the three components are labeled A, H and V inrelation to the local vertical reference frame. Local vertical can betransformed into the LOS coordinate frame or vice versa based on therange components of the NED coordinate frame.

Upon detect and track module 104 (FIG. 1) detecting an object, trackstate estimator 120 of FIG. 2 is configured to receive the correspondingelevation angle ε_(el) azimuth angle ε_(az) of the potential object ofcollision and is configured to receive positional and velocityinformation from inertial navigation system 105. Based on thisinformation, track state estimator 120 determines the position vector P_(OBJ,LV) and the velocity vector V _(OBJ,LV) of the potential object ofcollision in local vertical coordinates.

Track state estimator 120 uses these position and velocity values of thepotential object of collision and position and velocity values of UAV102 to calculate the relative range vector R of the potential impedimentwith respect to UAV 102, the relative range rate vector {dot over ( R,the line of sight rate vector {dot over ( λ, the line of sight anglevector λ, the range magnitude R and the range rate {dot over (R)}. Thevalues of relative range vector, relative range rate vector, line ofsight angle vector and line of sight rate vector are all computed intolocal vertical coordinates. For example local vertical coordinates canbe based on a North, East, Down (NED) reference frame 404 as illustratedin FIG. 4-2.

The relative range vector R (illustrated in FIG. 5) and range ratevector {dot over ( R are the differences between the position andvelocity of the potential object of collision and the position andvelocity of UAV 102 as illustrated in the following equation:

R= P _(OBJ,LV) − P _(UAV,LV)   Equation 2

{dot over ( R= V _(OBJ,LV) − V _(UAV,LV)   Equation 3

The line of sight angle vector λ is calculated by:

$\begin{matrix}{\lambda_{D} = {{arc}\; {\tan \left( {R_{E},R_{N}} \right)}}} & {{Equation}\mspace{14mu} 4} \\{\lambda_{E} = {{arc}\; {\tan \left( {{- R_{D}},\sqrt{R_{N}^{2} + R_{E}^{2}}} \right)}}} & {{Equation}\mspace{14mu} 5}\end{matrix}$

where λ_(D) is the down component of the line of sight angle, λ_(E) isthe east component of the line of sight angle, R_(N) is the northcomponent of the range vector (shown in FIG. 5), R_(E) is the eastcomponent of the range vector (shown in FIG. 5) and R_(D) is the downcomponent of the range vector (shown in FIG. 5). The line of sight ratevector {dot over ( λ is the angular rate of change of the line of sightvector and is calculated by:

$\begin{matrix}{\overset{\_}{\overset{.}{\lambda}} = \frac{\overset{\_}{R} \times \overset{\_}{\overset{.}{R}}}{R^{2}}} & {{Equation}\mspace{14mu} 6}\end{matrix}$

where R is the relative range vector of the potential object ofcollision with respect to UAV 102, {dot over ( R the relative range ratevector of the potential object of collision with respect to UAV 102 andR is the magnitude of the relative range and is calculated by:

R=√{square root over (R_(N) ² +R _(E) ² +R _(D) ²)}  Equation 7

where R_(N) is the north component of the relative range, R_(E) is theeast component of the relative range and R_(D) is the down component ofthe relative range.

In accordance with an embodiment of the present invention, avoid statecalculator 124 receives the relative range magnitude R, the relativerange rate {dot over (R)} and the line of sight rate vector {dot over (λ as determined and calculated by track state estimator 120.

Avoid state calculator 124 calculates a closing velocity V_(C) and atime-to-go t_(go) based on the relative range R and relative range rate{dot over (R)}. The closing velocity is the relative velocity along theline of sight between UAV 102 and the potential object of collision.Closing velocity is equal to the relative range rate provided by trackstate estimator 120 and is calculated by:

$\begin{matrix}{V_{C} = {- \frac{\overset{\_}{R} \cdot \overset{\_}{\overset{.}{R}}}{R}}} & {{Equation}\mspace{14mu} 8}\end{matrix}$

where R is the relative range vector, {dot over ( R is the relativerange rate vector and R is the relative range magnitude.

Time-to-go t_(go) is the amount of time until UAV 102 is at its closestpoint of approach to the potential object of collision assuming both thepotential object of collision and UAV 102 continue at constantnon-accelerating velocities. Time-to-go is calculated by:

$\begin{matrix}{t_{go} = \frac{R}{V_{C}}} & {{Equation}\mspace{14mu} 9}\end{matrix}$

where R is the magnitude of the relative range vector and V_(C) is theclosing velocity as calculated in Equation 8. The calculation of closingvelocity and the calculating of time-to-go are used for guiding UAV 102away from an object as well as in the calculation of ZEM.

Avoid state calculator 124 also calculates ZEM of UAV 102. ZEM is theestimated zero miss distance or closest point of approach vector thatUAV 102 will be with respect to the potential object of collision basedon current velocity and range profiles. ZEM is calculated by:

ZEM={dot over ( λ V _(C) t _(go) ²   Equation 10

where {dot over ( λ is the relative range rate vector of UAV 102, V_(C)is the closing velocity as calculated by Equation 8 and t_(go) istime-to-go as calculated in Equation 9.

Referring back to FIG. 2, auto avoid monitor 122 includes an avoid alertcalculator 126 configured to determine when a head-on flag and an avoidalert flag should be activated. To activate an avoid alert flag, avoidalert calculator 126 compares the magnitude of ZEM to the predeterminedmiss distance limit, such as 500 feet, or a predetermined allowable missdistance from the potential object of collision. If the ZEM is greaterthan the predetermined allowable miss distance, then the avoid alertflag is not activated. If, however, the ZEM is less than thepredetermined allowable miss distance, then the avoid alert flag isactivated. The alert flag remains activated until the ZEM becomesgreater than the predetermined deactivation distance, which is greaterthan the allowable miss distance. This creates a hysterisis effect thatprevents the alert flag from entering a cycle in which it is activatedand deactivated repeatedly.

Upon auto avoid guidance 128 receiving an avoid alert flag from avoidalert calculator 126 and/or a head-on flag, auto avoid guidance 128begins a guidance logic routine that continues as long as auto avoidmonitor 122 predicts that UAV 102 will approach an object within thepredetermined miss distance. FIG. 6 illustrates such a routine 600 asimplemented by auto avoid guidance 128 in accordance with an embodimentof the present invention.

Routine 600 begins at block 602 and determines whether an avoid alertflag has been activated by auto avoid calculator 126. If an avoid alertflag is activated, then control passes to block 614 to determine if ahead-on flag has been activated. Routine 600 continues to determine ifan avoid alert flag has been activated until auto avoid calculatoractivates an avoid alert flag.

If a head-on flag is activated, then routine 600 proceeds to block 604initializes head-on avoidance. At block 604, a head-on collisionmaneuver under auto avoid guidance is activated and a waypoint leg iscalculated. A waypoint leg is calculated which consists of at least twowaypoints parallel to the current vehicle heading that are offset by apredetermined amount to ensure that the miss distance is achieved. Aftercalculation of the waypoint leg, auto avoid guidance 128 begins guidanceof UAV 102 at block 606. At block 608, the routine determines whetherthe avoid alert flag is still activated. If the avoid alert flag isstill activated, then the routine passes to block 610 to determine ifthe final waypoint of the waypoint leg has been reached. If the avoidalert flag is not activated, then control passes to block 612 and autoavoid guidance returns UAV 102 back to the stored or previous guidancemode as set in initialization. If the final waypoint leg has beenreached, then control also passes to block 612. If the final waypointhas not been reached, then control passes back to block 606 to continueauto avoid guidance. The routine passes through blocks 608 and 610 untileither the avoid alert flag is not activated or the final waypoint hasbeen reached.

Referring back to block 614, if, however, a head-on flag is notactivated, then the routine passes to block 616 to initialize avoidance.At block 618, an inverse homing command is calculated and designed toguide UAV 102 off of the collision trajectory it is on. Under theinverse homing commands, auto avoid guidance 128 alters UAV 102 awayfrom the object of collision and recalculates the ZEM to determine ifUAV 102 is still on course to collide with the object of collision. Ifthe recalculation still indicates that UAV 102 is on course to collide,then auto avoid guidance repeats altering UAV 102 away from the objectof collision until UAV 102 Is no longer on course to collide with anobject of collision.

The calculated acceleration commands are generated normal to the currentline of sight vector to the object of collision as shown below:

$\begin{matrix}{n_{c} = \frac{- {N\left( {{ZEM}_{Desired} - {ZEM}} \right)}}{t_{go}^{2}}} & {{Equation}\mspace{14mu} 11}\end{matrix}$

where n_(c) is the acceleration command in local vertical coordinates, Nis the guidance gain for avoidance, ZEM is the current Zero Effort Missas calculated in Equation 10 by auto avoid monitor 122, ZEM_(Desired) isthe desired zero effort miss, and t_(go) is the time to go as calculatedin Equation 9 by the auto avoid monitor 122. ZEM_(Desired) is mostappropriately defined in the LOS frame (illustrated in FIG. 5) and thentransformed into the local vertical frame to support the previouscalculation.

At block 620, the routine determines if the alert avoid flag is stillactivated. If the avoid alert flag is still activated, then controlpasses back to block 618 to continue guiding UAV 102 away from theobject of collision. If, however, the alert avoid flag is not activated,then control passes to block 612 to return UAV 102 back to the stored orprevious guidance mode.

Although the present invention has been described in detail with respectto a control system for an unmanned aerial vehicle, the presentinvention is applicable to any vehicle control system or autopilot. Inaddition, although not specifically described, in one embodiment of thepresent invention, auto avoid guidance 128 (FIG. 2) supplies flightcontrols 114 (FIG. 2) with acceleration vectors in order to guide UAV102 away from an object of collision. This acceleration vector can beused to accommodate any vehicle control system. If a particular vehiclecontrol system does not accept an acceleration vector for its autopilot,the acceleration vector can be translated into a suitable parameter inorder to guide a vehicle away from an object of collision.

Although the present invention has been described with reference topreferred embodiments, workers skilled in the art will recognize thatchanges may be made in form and detail without departing from the spiritand scope of the invention.

1. An autonomous collision avoidance system for an unmanned aerialvehicle comprising: a detect and track module that senses a potentialobject of collision and that generates a moving object track for thepotential object of collision; an inertial navigation system thatprovides information indicative of a position and a velocity of theunmanned aerial vehicle; and an auto avoidance module that receives themoving object track for the potential object of collision and theinformation indicative of the position and the velocity of the unmannedaerial vehicle, the auto avoidance system utilizing the moving objecttrack of the potential object of collision and the informationindicative of the position and the velocity of the unmanned aerialvehicle to generate a guidance maneuver command that facilitates theunmanned aerial vehicle avoiding the potential object of collision. 2.The system of claim 1, further comprising: flight controls that receivethe guidance maneuver command and that utilize the guidance maneuvercommand to re-direct a course of the unmanned aerial vehicle to avoidthe potential object of collision.
 3. The system of claim 1, wherein theauto avoidance module includes a track state estimator that receives themoving object track in a form of an elevation angle and an azimuthdirection finding angle.
 4. The system of claim 3, wherein the elevationangle and the azimuth direction finding angle are relative to a sensorbore sight.
 5. The system of claim 1, wherein the inertial navigationsystem includes a global positioning system and an inertial measurementunit.
 6. The system of claim 1, wherein the auto avoidance moduleincludes an auto avoid recovery unit that generates a recovery command,the recovery command returning the unmanned aerial vehicle to a previousguidance mode.
 7. A method for autonomously controlling an unmannedaerial vehicle comprising: utilizing a sensor to scan for a potentialobject of collision; utilizing data collected from the sensor togenerate a moving object track for the potential object of collision;determining a position and a velocity of the unmanned aerial vehicle;generating an estimate of a position and a velocity of the potentialobject of collision based at least in part on the moving object trackand on the position and velocity of the unmanned aerial vehicle;performing a calculation so as to determine whether the unmanned aerialvehicle is on a course to enter within a predetermined distance relativeto the potential object of collision; and altering the course of theunmanned aerial vehicle based at least in part on the calculation. 8.The method of claim 7, further comprising: repeating said performing andsaid altering until the unmanned aerial vehicle is on course to notenter within the predetermined distance relative to the potential objectof collision.
 9. The method of claim 7, wherein altering the coursecomprises guiding the unmanned aerial vehicle away from the potentialobject of collision according to civilian aircraft operating rules. 10.The method of claim 7, wherein altering the course comprises calculatinga waypoint leg to alter the course of the unmanned aerial vehicle. 11.The method of claim 7, further comprising: restoring a previous courseof the unmanned aerial vehicle after the unmanned aerial vehicle hasavoided the potential object of collision.
 12. The method of claim 7,further comprising: sending an indication of a collision status from theunmanned aerial vehicle to a ground control station.
 13. An autonomouscollision avoidance system for an unmanned aerial vehicle comprising: asensor that detects an elevation angle and an azimuth angle of apotential object of collision; an inertial navigation system thatprovides information indicative of a velocity, a position, and anangular position of the unmanned aerial vehicle; and a track stateestimator that receives information indicative of the potential objectof collision elevation angle, the potential object of collision azimuthangle, the unmanned aerial vehicle velocity, the unmanned aerial vehicleposition, and the unmanned aerial vehicle angular position, the trackstate estimator utilizing the received information to determine a lineof sight rate vector, a relative range magnitude, and a relative rangerate of the unmanned aerial vehicle relative to the potential object ofcollision.
 14. The system of claim 13, further comprising: an avoidstate calculator that receives information indicative of the line ofsight rate vector, the relative range magnitude, and the relative rangerate, the avoid state calculator utilizing the received information todetermine a zero effort miss distance of the unmanned aerial vehiclerelative to the potential object of collision.
 15. The system of claim14, further comprising: an avoid alert calculator that receives the zeroeffort miss distance and that compares the zero effort miss distance toa predetermined allowable miss distance, the avoid alert calculatorgenerating an alert flag upon the zero effort miss distance being lessthan the predetermined allowable miss distance.
 16. The system of claim15, further comprising: an auto avoid guidance module that, uponreceiving the alert flag, generates a command to re-direct a course ofthe unmanned aerial vehicle to avoid the potential object of collision.17. The system of claim 16, further comprising: an auto avoid recoveryunit that generates a recovery command that returns the unmanned aerialvehicle to a previous guidance mode.
 18. The system of claim 15, whereinan indication of the alert flag is sent to a ground station.
 19. Thesystem of claim 15, wherein the alert flag indicates a head-oncollision.
 20. The system of claim 15, wherein the alert flag indicatesa non-head-on collision.